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CycleGAN Day-to-Night Image Translation by IAES IJAI is a document available to read on EtoBox.

What is CycleGAN Day-to-Night Image Translation about?

This study investigates day-to-night image translation using a hybrid approach that combines traditional image processing with CycleGAN-based deep learning models. It compares various CycleGAN architectures, including the original CycleGAN, FPN-CycleGAN, and UVCGAN, to determine their effectiveness in generating synthetic nighttime images. Results indicate that the UVCGAN model outperforms others in terms of image quality, as evidenced by its superior FID score.

Author

IAES IJAI

Language

EN